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https://issues.apache.org/jira/browse/HIVE-9188?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14264436#comment-14264436
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Hive QA commented on HIVE-9188:
-------------------------------
{color:green}Overall{color}: +1 all checks pass
Here are the results of testing the latest attachment:
https://issues.apache.org/jira/secure/attachment/12690039/HIVE-9188.4.patch
{color:green}SUCCESS:{color} +1 6748 tests passed
Test results:
http://ec2-174-129-184-35.compute-1.amazonaws.com/jenkins/job/PreCommit-HIVE-TRUNK-Build/2250/testReport
Console output:
http://ec2-174-129-184-35.compute-1.amazonaws.com/jenkins/job/PreCommit-HIVE-TRUNK-Build/2250/console
Test logs:
http://ec2-174-129-184-35.compute-1.amazonaws.com/logs/PreCommit-HIVE-TRUNK-Build-2250/
Messages:
{noformat}
Executing org.apache.hive.ptest.execution.PrepPhase
Executing org.apache.hive.ptest.execution.ExecutionPhase
Executing org.apache.hive.ptest.execution.ReportingPhase
{noformat}
This message is automatically generated.
ATTACHMENT ID: 12690039 - PreCommit-HIVE-TRUNK-Build
> BloomFilter in ORC row group index
> ----------------------------------
>
> Key: HIVE-9188
> URL: https://issues.apache.org/jira/browse/HIVE-9188
> Project: Hive
> Issue Type: New Feature
> Components: File Formats
> Affects Versions: 0.15.0
> Reporter: Prasanth Jayachandran
> Assignee: Prasanth Jayachandran
> Labels: orcfile
> Attachments: HIVE-9188.1.patch, HIVE-9188.2.patch, HIVE-9188.3.patch,
> HIVE-9188.4.patch
>
>
> BloomFilters are well known probabilistic data structure for set membership
> checking. We can use bloom filters in ORC index for better row group pruning.
> Currently, ORC row group index uses min/max statistics to eliminate row
> groups (stripes as well) that do not satisfy predicate condition specified in
> the query. But in some cases, the efficiency of min/max based elimination is
> not optimal (unsorted columns with wide range of entries). Bloom filters can
> be an effective and efficient alternative for row group/split elimination for
> point queries or queries with IN clause.
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